Rudhir Gupta

Papers

Total Citations

704

H-Index

About

Rudhir Gupta is a researcher whose work sits at the intersection of computer vision, robotics, and human activity understanding. His most influential contribution focuses on the challenge of extracting meaningful information from RGB-D video data — a problem of critical importance for personal robots operating alongside humans in everyday environments. His 2013 paper, "Learning Human Activities and Object Affordances from RGB-D Videos," has accumulated an impressive 699 citations, reflecting the significant impact this work has had on the research community. By tackling the dual challenge of recognizing sequences of human sub-activities and inferring how objects can be functionally used — known as object affordances — Gupta's research provided a foundational framework for enabling robots to better interpret and anticipate human behavior. This line of work addresses one of robotics' most enduring challenges: giving machines the perceptual and reasoning capabilities needed to understand not just what people are doing, but how objects relate to those actions. His contributions have proven highly relevant to researchers working in activity recognition, human-robot interaction, and scene understanding, making his work a frequently referenced touchstone in these rapidly evolving fields.